layout: true <div class="my-footer"><span>kathoffman.github.io/swimmer-plots/slides.html</span></div> --- name: xaringan-title class: right, middle background-image: url(img/blue-foaming-waves-north-beach-nazare-portugal.jpg) background-size: cover <h1 style="color: white;">Making swimmer plots for longitudinal data using {ggplot}</h1> <img src="img/rmed-hex.png" alt="Rmed-hex-sticker" width="180" /> <h3 style="color: white;"> Kat Hoffman | August 25, 2022</h3> --- class: middle, center <img src="img/climbing_comic.jpeg" width="350"/> ### Find me at: [<svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M172.5 131.1C228.1 75.51 320.5 75.51 376.1 131.1C426.1 181.1 433.5 260.8 392.4 318.3L391.3 319.9C381 334.2 361 337.6 346.7 327.3C332.3 317 328.9 297 339.2 282.7L340.3 281.1C363.2 249 359.6 205.1 331.7 177.2C300.3 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style="height:1em;width:0.97em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3 .3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5 .3-6.2 2.3zm44.2-1.7c-2.9 .7-4.9 2.6-4.6 4.9 .3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3 .7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3 .3 2.9 2.3 3.9 1.6 1 3.6 .7 4.3-.7 .7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3 .7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3 .7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg> @kathoffman](http://github.com/kathoffman) [<svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M511.6 36.86l-64 415.1c-1.5 9.734-7.375 18.22-15.97 23.05c-4.844 2.719-10.27 4.097-15.68 4.097c-4.188 0-8.319-.8154-12.29-2.472l-122.6-51.1l-50.86 76.29C226.3 508.5 219.8 512 212.8 512C201.3 512 192 502.7 192 491.2v-96.18c0-7.115 2.372-14.03 6.742-19.64L416 96l-293.7 264.3L19.69 317.5C8.438 312.8 .8125 302.2 .0625 289.1s5.469-23.72 16.06-29.77l448-255.1c10.69-6.109 23.88-5.547 34 1.406S513.5 24.72 511.6 36.86z"/></svg> kathoffman.stats@gmail.com](mailto:kathoffman.stats@gmail.com) --- # Swimmer plot .pull-left[ - Graphical way to show a **subject's profile over time** - A series of horizontal lines, in which **each line represents one subject** - **Colors or shapes** on the line **indicate treatments** or other statuses of that subject at a particular time ] .pull-right[ <div class="figure" style="text-align: center"> <img src="img/cell_swimmer.png" alt="Image: Shen et al. Cell 182, 59–72, July 9, 2020" width="600" /> <p class="caption">Image: Shen et al. Cell 182, 59–72, July 9, 2020</p> </div> ] <!-- -- --> <!-- - --> <!-- -- --> <!-- - --> <!-- -- --> <!-- - Excellent for exploratory data analysis (EDA) of longitudinal data (e.g. visualize missigness or sampling patterns) --> <!-- -- --> <!-- - Can be included as a final product (e.g. manuscripts, presentations) to explain cohort composition, treatment variability, and more --> <!-- -- --> <!-- - While `R` packages such as `swimmer` exist, it is often faster and more customizable to write end-to-end `ggplot` code yourself --> --- # Do we *really* have to hand-code this? .pull-left[ - `R` packages such as `swimplot` do exist, but it is more customizable to write end-to-end `ggplot` code yourself - Configuring the legend correctly in `ggplot` can be tricky whether you use `swimplot` or not ] .pull-right[ <div class="figure"> <img src="img/swimmer_swimplot.png" alt="Image courtesy of {swimplot} vignette." width="500" /> <p class="caption">Image courtesy of {swimplot} vignette.</p> </div> ] --- .left-column[ ### Today's swimmer plot: We will show the timing of... - severe hypoxia - intubation - steroids administration - 28-day mortality ...in a cohort of hospitalized COVID-19 patients. ] .right-column[ <img src="img/swimmer.png" width="700" style="display: block; margin: auto;" /> ] --- # Step 1: Long-form data set .pull-left[ - ID column - Time column (e.g. day) - One column per status (e.g. drug A - yes/no, drug B - yes/no) - One row per subject per unit of time ] -- .pull-right[ ```r library(tidyverse) library(data.table) dat_long <- read_csv("https://raw.githubusercontent.com/kathoffman/steroids-trial-emulation/main/data/dat_trt_timeline.csv",col_types = list(id = "c", steroids = "c", death = "c", severe = "c")) dat_long |> data.table() ``` ``` id day intubation_status steroids death severe 1: 797 0 Not intubated 0 0 0 2: 797 1 Not intubated 0 0 0 3: 797 2 Not intubated 0 0 1 4: 797 3 Not intubated 0 0 0 5: 797 4 Not intubated 0 0 0 --- 415: 664 27 Not intubated 0 0 0 416: 664 28 Not intubated 0 0 0 417: 373 0 Not intubated 0 0 0 418: 373 1 Not intubated 0 0 0 419: 373 2 Not intubated 0 0 0 ``` ] --- # Step 2: Long-form data for plotting .pull-left[ - ID column (**optional: order by maximum time per subject**) - Time column - One column per status, **which is now the time if you want the status to be marked on the plot** - One row per subject per unit of time ] -- .pull-right[ This is a way to create data with a reordered patient ID (by hospital length-of-stay): ```r dat_reorder <- dat_long |> group_by(id) |> mutate(max_day = max(day)) |> ungroup() |> mutate(id = fct_reorder(factor(id), max_day)) ``` The next slide shows how to change the status columns to `{status}_this_day` columns. ] --- # Step 2: Long-form data for plotting ```r dat_swim <- dat_reorder |> mutate(severe_this_day = case_when(severe == 1 ~ day), steroids_this_day = case_when(steroids == 1 ~ day), death_this_day = case_when(death == 1 ~ day)) dat_swim |> 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<!-- --> ] --- count: false # Step 3: Plot all your geometries .panel1-swim0-user[ ```r dat_swim %>% ggplot(aes(y=id, group=id)) + theme_bw() + * geom_line(aes(x=day, col = intubation_status)) ``` ] .panel2-swim0-user[ <!-- --> ] --- count: false # Step 3: Plot all your geometries .panel1-swim0-user[ ```r dat_swim %>% ggplot(aes(y=id, group=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status)) + * geom_point(aes(x=steroids_this_day)) ``` ] .panel2-swim0-user[ <!-- --> ] --- count: false # Step 3: Plot all your geometries .panel1-swim0-user[ ```r dat_swim %>% ggplot(aes(y=id, group=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status)) + geom_point(aes(x=steroids_this_day)) + * geom_point(aes(x=severe_this_day)) ``` ] .panel2-swim0-user[ <!-- --> ] --- count: false # Step 3: Plot all your geometries .panel1-swim0-user[ ```r dat_swim %>% ggplot(aes(y=id, group=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status)) + geom_point(aes(x=steroids_this_day)) + geom_point(aes(x=severe_this_day)) + * geom_point(aes(x=death_this_day)) ``` ] .panel2-swim0-user[ <!-- --> ] <style> .panel1-swim0-user { color: black; width: 38.6060606060606%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel2-swim0-user { color: black; width: 59.3939393939394%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel3-swim0-user { color: black; width: NA%; hight: 33%; float: left; padding-left: 1%; font-size: 80% } </style> --- count: false # Step 4: Modify geom_* layers. .panel1-swim1-user[ ```r *dat_swim %>% * ggplot(aes(y=id, group=id)) + * theme_bw() ``` ] .panel2-swim1-user[ <!-- --> ] --- count: false # Step 4: Modify geom_* layers. .panel1-swim1-user[ ```r dat_swim %>% ggplot(aes(y=id, group=id)) + theme_bw() + * geom_line(aes(x=day, col = intubation_status), * size=1.8) ``` ] .panel2-swim1-user[ <!-- --> ] --- count: false # Step 4: Modify geom_* layers. .panel1-swim1-user[ ```r dat_swim %>% ggplot(aes(y=id, group=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status), size=1.8) + * geom_point(aes(x=steroids_this_day), * stroke=2, * shape = 15) ``` ] .panel2-swim1-user[ <!-- --> ] --- count: false # Step 4: Modify geom_* layers. .panel1-swim1-user[ ```r dat_swim %>% ggplot(aes(y=id, group=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status), size=1.8) + geom_point(aes(x=steroids_this_day), stroke=2, shape = 15) + * geom_point(aes(x=severe_this_day), * size=2, * stroke=1.5, * shape = 21) ``` ] .panel2-swim1-user[ <!-- --> ] --- count: false # Step 4: Modify geom_* layers. .panel1-swim1-user[ ```r dat_swim %>% ggplot(aes(y=id, group=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status), size=1.8) + geom_point(aes(x=steroids_this_day), stroke=2, shape = 15) + geom_point(aes(x=severe_this_day), size=2, stroke=1.5, shape = 21) + * geom_point(aes(x=death_this_day), * size=2, * stroke=1.5, * shape = 4) ``` ] .panel2-swim1-user[ <!-- --> ] <style> .panel1-swim1-user { color: black; width: 38.6060606060606%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel2-swim1-user { color: black; width: 59.3939393939394%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel3-swim1-user { color: black; width: NA%; hight: 33%; float: left; padding-left: 1%; font-size: 80% } </style> --- # Step 5: Add colors and legend .left-column[  ] .right-column[ **The Big Picture:** - We want a legend which correctly maps each shape, color, and line type to the corresponding status. - We need all of our statuses to show up in the legend. They currently do not, because they're not being mapped to an `aes`thetic argument. - We will force all the statuses to show up by creating a new aesthetic (color) which **corresponds to the name we want each status to be labeled** in the legend. - We will then modify this legend for "color" to also contain information about shape, linetype, etc. for each status. ] --- count: false # Step 5: Add colors and legend .panel1-swim2-user[ ```r *dat_swim %>% * ggplot(aes(y=id)) + * theme_bw() + * geom_line(aes(x=day, * col = intubation_status, * group=id), * size=1.8) ``` ] .panel2-swim2-user[ <!-- --> ] --- count: false # Step 5: Add colors and legend .panel1-swim2-user[ ```r dat_swim %>% ggplot(aes(y=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status, group=id), size=1.8) + * geom_point(aes(x=steroids_this_day, * col="Steroids"), * stroke=2, * shape=15) ``` ] .panel2-swim2-user[ <!-- --> ] --- count: false # Step 5: Add colors and legend .panel1-swim2-user[ ```r dat_swim %>% ggplot(aes(y=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status, group=id), size=1.8) + geom_point(aes(x=steroids_this_day, col="Steroids"), stroke=2, shape=15) + * geom_point(aes(x=severe_this_day, * col="Severe hypoxia"), * size=2, * stroke=1.5, * shape=21) ``` ] .panel2-swim2-user[ <!-- --> ] --- count: false # Step 5: Add colors and legend .panel1-swim2-user[ ```r dat_swim %>% ggplot(aes(y=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status, group=id), size=1.8) + geom_point(aes(x=steroids_this_day, col="Steroids"), stroke=2, shape=15) + geom_point(aes(x=severe_this_day, col="Severe hypoxia"), size=2, stroke=1.5, shape=21) + * geom_point(aes(x=death_this_day, * col="Death"), * size=2, * stroke=1.5, * shape=4) ``` ] .panel2-swim2-user[ <!-- --> ] <style> .panel1-swim2-user { color: black; width: 38.6060606060606%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel2-swim2-user { color: black; width: 59.3939393939394%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel3-swim2-user { color: black; width: NA%; hight: 33%; float: left; padding-left: 1%; font-size: 80% } </style> --- # Step 6: Modify colors - We now need a key for status labels and corresponding colors. ```r # define colors for all geometries with a color argument cols <- c("Severe hypoxia" = "#b24745", # red "Intubated" = "#483d8b", # navy "Not intubated" = "#74aaff", # blue "Steroids"="#ffd966", # gold "Death" = "#000000") # black ``` - The label of the status should match the label inputted to `aes(col = "...")`. - The order of this color key will be the order the statuses appear in the legend. - We will use this key as the `values` argument of `scale_color_manual()`: --- count: false # Step 6: Modify colors .panel1-swim3-user[ ```r *dat_swim %>% * ggplot(aes(y=id)) + * theme_bw() + * geom_line(aes(x=day, * col = intubation_status, * group=id), * size=1.8) + * geom_point(aes(x=steroids_this_day, * col="Steroids"), * stroke=2, * shape=15) + * geom_point(aes(x=severe_this_day, * col="Severe hypoxia"), * size=2, * stroke=1.5, * shape=21) + * geom_point(aes(x=death_this_day, * col="Death"), * size=2, * stroke=1.5, * shape=4) ``` ] .panel2-swim3-user[ <!-- --> ] --- count: false # Step 6: Modify colors .panel1-swim3-user[ ```r dat_swim %>% ggplot(aes(y=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status, group=id), size=1.8) + geom_point(aes(x=steroids_this_day, col="Steroids"), stroke=2, shape=15) + geom_point(aes(x=severe_this_day, col="Severe hypoxia"), size=2, stroke=1.5, shape=21) + geom_point(aes(x=death_this_day, col="Death"), size=2, stroke=1.5, shape=4) + * scale_color_manual(values = cols, * name="Patient Status") ``` ] .panel2-swim3-user[ <!-- --> ] <style> .panel1-swim3-user { color: black; width: 38.6060606060606%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel2-swim3-user { color: black; width: 59.3939393939394%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel3-swim3-user { color: black; width: NA%; hight: 33%; float: left; padding-left: 1%; font-size: 80% } </style> --- # Step 7: Modify legend using override.aes() - We need to create vectors for overriding the aesthetics for `shape`, `linetype`, `stroke`, and `size` in the current "color" legend. - These should be in the same order as the `cols` key - If we don't want a certain aesthetic to show up (e.g. no shape for intubation), we use `NA` ```r cols ``` ``` Severe hypoxia Intubated Not intubated Steroids Death "#b24745" "#483d8b" "#74aaff" "#ffd966" "#000000" ``` ```r shape_override <- c(21, NA, NA, 15, 4) # order matches `cols`:severe, intubation (yes/no), steroids, death line_override <- c(NA,1,1,NA,NA) # order matches `cols`:severe, intubation (yes/no), steroids, death stroke_override <- c(.8,1,1,1,1) # order matches `cols`:severe, intubation (yes/no), steroids, death size_override <- c(2.5,2.5,2.6,2,2) # order matches `cols`:severe, intubation (yes/no), steroids, death ``` --- count: false # Step 7: Modify legend using override.aes() .panel1-swim4-user[ ```r *dat_swim %>% * ggplot(aes(y=id)) + * theme_bw() + * geom_line(aes(x=day, col = intubation_status, group=id), * size=1.8) + * geom_point(aes(x=steroids_this_day, col="Steroids"), * stroke=2, shape=15) + * geom_point(aes(x=severe_this_day, col="Severe hypoxia"), * size=2, stroke=1.5, shape=21) + * geom_point(aes(x=death_this_day, col="Death"), * size=2, stroke=1.5, shape=4) + * scale_color_manual(values = cols, * name="Patient Status") ``` ] .panel2-swim4-user[ <!-- --> ] --- count: false # Step 7: Modify legend using override.aes() .panel1-swim4-user[ ```r dat_swim %>% ggplot(aes(y=id)) + theme_bw() + geom_line(aes(x=day, col = intubation_status, group=id), size=1.8) + geom_point(aes(x=steroids_this_day, col="Steroids"), stroke=2, shape=15) + geom_point(aes(x=severe_this_day, col="Severe hypoxia"), size=2, stroke=1.5, shape=21) + geom_point(aes(x=death_this_day, col="Death"), size=2, stroke=1.5, shape=4) + scale_color_manual(values = cols, name="Patient Status") + * guides(color = guide_legend( * override.aes = list( * stroke = stroke_override, * size = size_override, * shape = shape_override, * linetype = line_override) * )) ``` ] .panel2-swim4-user[ <!-- --> ] <style> .panel1-swim4-user { color: black; width: 38.6060606060606%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel2-swim4-user { color: black; width: 59.3939393939394%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel3-swim4-user { color: black; width: NA%; hight: 33%; float: left; padding-left: 1%; font-size: 80% } </style> --- count: false # Step 8: Make minor theme edits .panel1-swim5-user[ ```r *p + labs(x="Days since hospitalization", * y="Patient\nnumber", * title="Treatment Timeline for N=30 Patients") ``` ] .panel2-swim5-user[ <!-- --> ] --- count: false # Step 8: Make minor theme edits .panel1-swim5-user[ ```r p + labs(x="Days since hospitalization", y="Patient\nnumber", title="Treatment Timeline for N=30 Patients") + * scale_x_continuous(expand=c(0,0)) ``` ] .panel2-swim5-user[ <!-- --> ] --- count: false # Step 8: Make minor theme edits .panel1-swim5-user[ ```r p + labs(x="Days since hospitalization", y="Patient\nnumber", title="Treatment Timeline for N=30 Patients") + scale_x_continuous(expand=c(0,0)) + * theme(text=element_text(family="Poppins", size=11)) + * theme(title = element_text(angle = 0, vjust=.5, * size=12, face="bold"), * axis.title.y = element_text(angle = 0, vjust=.5, * size=12, face="bold"), * axis.title.x = element_text(size=15, face="bold", * vjust=-0.5, hjust=0), * axis.text.y = element_text(size=6, * hjust=1.5), * axis.ticks.y = element_blank()) ``` ] .panel2-swim5-user[ <!-- --> ] --- count: false # Step 8: Make minor theme edits .panel1-swim5-user[ ```r p + labs(x="Days since hospitalization", y="Patient\nnumber", title="Treatment Timeline for N=30 Patients") + scale_x_continuous(expand=c(0,0)) + theme(text=element_text(family="Poppins", size=11)) + theme(title = element_text(angle = 0, vjust=.5, size=12, face="bold"), axis.title.y = element_text(angle = 0, vjust=.5, size=12, face="bold"), axis.title.x = element_text(size=15, face="bold", vjust=-0.5, hjust=0), axis.text.y = element_text(size=6, hjust=1.5), axis.ticks.y = element_blank()) + * theme(legend.position = c(0.8, 0.3), * legend.title = element_text(colour="black", * size=13, * face=4), * legend.text = element_text(colour="black", * size=10), * legend.background = element_rect(size=0.5, * linetype="solid", * colour ="gray30")) ``` ] .panel2-swim5-user[ <!-- --> ] --- count: false # Step 8: Make minor theme edits .panel1-swim5-user[ ```r p + labs(x="Days since hospitalization", y="Patient\nnumber", title="Treatment Timeline for N=30 Patients") + scale_x_continuous(expand=c(0,0)) + theme(text=element_text(family="Poppins", size=11)) + theme(title = element_text(angle = 0, vjust=.5, size=12, face="bold"), axis.title.y = element_text(angle = 0, vjust=.5, size=12, face="bold"), axis.title.x = element_text(size=15, face="bold", vjust=-0.5, hjust=0), axis.text.y = element_text(size=6, hjust=1.5), axis.ticks.y = element_blank()) + theme(legend.position = c(0.8, 0.3), legend.title = element_text(colour="black", size=13, face=4), legend.text = element_text(colour="black", size=10), legend.background = element_rect(size=0.5, linetype="solid", colour ="gray30")) + * theme(panel.grid.minor = element_blank(), * panel.grid.major.x = element_blank() * ) ``` ] .panel2-swim5-user[ <!-- --> ] <style> .panel1-swim5-user { color: black; width: 38.6060606060606%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel2-swim5-user { color: black; width: 59.3939393939394%; hight: 32%; float: left; padding-left: 1%; font-size: 80% } .panel3-swim5-user { color: black; width: NA%; hight: 33%; float: left; padding-left: 1%; font-size: 80% } </style> --- # In Summary 🏊 .pull-left[ - Long-format plotting data will need to have one column per status per row which indicates the **time of the status marker** to be denoted. - Once data is properly formatted, `ggplot` can be used to make customizable swimmer plots with the `geom_line` and `geom_point` layers. - The legend can be properly configured using the `override.aes()` argument in `guides()`. - These ideas can be extended in many ways, such as [**showing the pattern of missing data**](https://www.khstats.com/blog/trt-timelines/trt-timelines/). ] -- .pull-right[ <div class="figure"> <img src="img/trt-timeline-missing.png" alt="Image from Patient Treatment Timelines for Longitudinal Survival Data -- KHstats, 2019" width="400" /> <p class="caption">Image from Patient Treatment Timelines for Longitudinal Survival Data -- KHstats, 2019</p> </div> ] <!-- adjust font size in this css code chunk, currently 80 --> <style type="text/css"> .remark-code{line-height: 1.5; font-size: 80%} @media print { .has-continuation { display: block; } } code.r.hljs.remark-code{ position: relative; overflow-x: hidden; } code.r.hljs.remark-code:hover{ overflow-x:visible; width: 500px; border-style: solid; } </style> --- class: middle, center Thank you to the authors of `{xaringan}` and `{flipbookr}` for making these slides possible. <br> <br> <br> [<svg aria-hidden="true" role="img" viewBox="0 0 640 512" style="height:1em;width:1.25em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M172.5 131.1C228.1 75.51 320.5 75.51 376.1 131.1C426.1 181.1 433.5 260.8 392.4 318.3L391.3 319.9C381 334.2 361 337.6 346.7 327.3C332.3 317 328.9 297 339.2 282.7L340.3 281.1C363.2 249 359.6 205.1 331.7 177.2C300.3 145.8 249.2 145.8 217.7 177.2L105.5 289.5C73.99 320.1 73.99 372 105.5 403.5C133.3 431.4 177.3 435 209.3 412.1L210.9 410.1C225.3 400.7 245.3 404 255.5 418.4C265.8 432.8 262.5 452.8 248.1 463.1L246.5 464.2C188.1 505.3 110.2 498.7 60.21 448.8C3.741 392.3 3.741 300.7 60.21 244.3L172.5 131.1zM467.5 380C411 436.5 319.5 436.5 263 380C213 330 206.5 251.2 247.6 193.7L248.7 192.1C258.1 177.8 278.1 174.4 293.3 184.7C307.7 194.1 311.1 214.1 300.8 229.3L299.7 230.9C276.8 262.1 280.4 306.9 308.3 334.8C339.7 366.2 390.8 366.2 422.3 334.8L534.5 222.5C566 191 566 139.1 534.5 108.5C506.7 80.63 462.7 76.99 430.7 99.9L429.1 101C414.7 111.3 394.7 107.1 384.5 93.58C374.2 79.2 377.5 59.21 391.9 48.94L393.5 47.82C451 6.731 529.8 13.25 579.8 63.24C636.3 119.7 636.3 211.3 579.8 267.7L467.5 380z"/></svg> khstats.com](https://khstats.com) [<svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M459.4 151.7c.325 4.548 .325 9.097 .325 13.65 0 138.7-105.6 298.6-298.6 298.6-59.45 0-114.7-17.22-161.1-47.11 8.447 .974 16.57 1.299 25.34 1.299 49.06 0 94.21-16.57 130.3-44.83-46.13-.975-84.79-31.19-98.11-72.77 6.498 .974 12.99 1.624 19.82 1.624 9.421 0 18.84-1.3 27.61-3.573-48.08-9.747-84.14-51.98-84.14-102.1v-1.299c13.97 7.797 30.21 12.67 47.43 13.32-28.26-18.84-46.78-51.01-46.78-87.39 0-19.49 5.197-37.36 14.29-52.95 51.65 63.67 129.3 105.3 216.4 109.8-1.624-7.797-2.599-15.92-2.599-24.04 0-57.83 46.78-104.9 104.9-104.9 30.21 0 57.5 12.67 76.67 33.14 23.72-4.548 46.46-13.32 66.6-25.34-7.798 24.37-24.37 44.83-46.13 57.83 21.12-2.273 41.58-8.122 60.43-16.24-14.29 20.79-32.16 39.31-52.63 54.25z"/></svg> @kat\_hoffman\_](http://twitter.com/kat_hoffman_) [<svg aria-hidden="true" role="img" viewBox="0 0 496 512" style="height:1em;width:0.97em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3 .3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5 .3-6.2 2.3zm44.2-1.7c-2.9 .7-4.9 2.6-4.6 4.9 .3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3 .7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3 .3 2.9 2.3 3.9 1.6 1 3.6 .7 4.3-.7 .7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3 .7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3 .7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"/></svg> @kathoffman](http://github.com/kathoffman) [<svg aria-hidden="true" role="img" viewBox="0 0 512 512" style="height:1em;width:1em;vertical-align:-0.125em;margin-left:auto;margin-right:auto;font-size:inherit;fill:currentColor;overflow:visible;position:relative;"><path d="M511.6 36.86l-64 415.1c-1.5 9.734-7.375 18.22-15.97 23.05c-4.844 2.719-10.27 4.097-15.68 4.097c-4.188 0-8.319-.8154-12.29-2.472l-122.6-51.1l-50.86 76.29C226.3 508.5 219.8 512 212.8 512C201.3 512 192 502.7 192 491.2v-96.18c0-7.115 2.372-14.03 6.742-19.64L416 96l-293.7 264.3L19.69 317.5C8.438 312.8 .8125 302.2 .0625 289.1s5.469-23.72 16.06-29.77l448-255.1c10.69-6.109 23.88-5.547 34 1.406S513.5 24.72 511.6 36.86z"/></svg> kathoffman.stats@gmail.com](mailto:kathoffman.stats@gmail.com) <img src="img/climbing_comic.jpeg" width="250"/>